Natural Language Processing for Adjudication of Heart Failure in a Multicenter Clinical Trial: A Secondary Analysis of a Randomized Clinical Trial.

Importance: The gold standard for outcome adjudication in clinical trials is medical record review by a physician clinical events committee (CEC), which requires substantial time and expertise. Automated adjudication of medical records by natural language processing (NLP) may offer a more resource-efficient alternative but this approach has not been validated in a multicenter setting. Objective: To externally validate the Community Care Cohort Project (C3PO) NLP model for heart failure (HF) hospitalization adjudication, which was previously developed and tested within one health care system, compared to gold-standard CEC adjudication in a multicenter clinical trial. Design, Setting, and Participants: This was a retrospective analysis of the Influenza Vaccine to Effectively Stop Cardio Thoracic Events and Decompensated Heart Failure (INVESTED) trial, which compared 2 influenza vaccines in 5260 participants with cardiovascular disease at 157 sites in the US and Canada between September 2016 and January 2019. Analysis was performed from November 2022 to October 2023. Exposures: Individual sites submitted medical records for each hospitalization. The central INVESTED CEC and the C3PO NLP model independently adjudicated whether the cause of hospitalization was HF using the prepared hospitalization dossier. The C3PO NLP model was fine-tuned (C3PO + INVESTED) and a de novo NLP model was trained using half the INVESTED hospitalizations. Main Outcomes and Measures: Concordance between the C3PO NLP model HF adjudication and the gold-standard INVESTED CEC adjudication was measured by raw agreement, κ, sensitivity, and specificity. The fine-tuned and de novo INVESTED NLP models were evaluated in an internal validation cohort not used for training. Results: Among 4060 hospitalizations in 1973 patients (mean [SD] age, 66.4 [13.2] years; 514 [27.4%] female and 1432 [72.6%] male]), 1074 hospitalizations (26%) were adjudicated as HF by the CEC. There was good agreement between the C3PO NLP and CEC HF adjudications (raw agreement, 87% [95% CI, 86-88]; κ, 0.69 [95% CI, 0.66-0.72]). C3PO NLP model sensitivity was 94% (95% CI, 92-95) and specificity was 84% (95% CI, 83-85). The fine-tuned C3PO and de novo NLP models demonstrated agreement of 93% (95% CI, 92-94) and κ of 0.82 (95% CI, 0.77-0.86) and 0.83 (95% CI, 0.79-0.87), respectively, vs the CEC. CEC reviewer interrater reproducibility was 94% (95% CI, 93-95; κ, 0.85 [95% CI, 0.80-0.89]). Conclusions and Relevance: The C3PO NLP model developed within 1 health care system identified HF events with good agreement relative to the gold-standard CEC in an external multicenter clinical trial. Fine-tuning the model improved agreement and approximated human reproducibility. Further study is needed to determine whether NLP will improve the efficiency of future multicenter clinical trials by identifying clinical events at scale.

Natural Language Processing for Adjudication of Heart Failure Hospitalizations in a Multi-Center Clinical Trial.

Background: The gold standard for outcome adjudication in clinical trials is chart review by a physician clinical events committee (CEC), which requires substantial time and expertise. Automated adjudication by natural language processing (NLP) may offer a more resource-efficient alternative. We previously showed that the Community Care Cohort Project (C3PO) NLP model adjudicates heart failure (HF) hospitalizations accurately within one healthcare system. Methods: This study externally validated the C3PO NLP model against CEC adjudication in the INVESTED trial. INVESTED compared influenza vaccination formulations in 5260 patients with cardiovascular disease at 157 North American sites. A central CEC adjudicated the cause of hospitalizations from medical records. We applied the C3PO NLP model to medical records from 4060 INVESTED hospitalizations and evaluated agreement between the NLP and final consensus CEC HF adjudications. We then fine-tuned the C3PO NLP model (C3PO+INVESTED) and trained a de novo model using half the INVESTED hospitalizations, and evaluated these models in the other half. NLP performance was benchmarked to CEC reviewer inter-rater reproducibility. Results: 1074 hospitalizations (26%) were adjudicated as HF by the CEC. There was high agreement between the C3PO NLP and CEC HF adjudications (agreement 87%, kappa statistic 0.69). C3PO NLP model sensitivity was 94% and specificity was 84%. The fine-tuned C3PO and de novo NLP models demonstrated agreement of 93% and kappa of 0.82 and 0.83, respectively. CEC reviewer inter-rater reproducibility was 94% (kappa 0.85). Conclusion: Our NLP model developed within a single healthcare system accurately identified HF events relative to the gold-standard CEC in an external multi-center clinical trial. Fine-tuning the model improved agreement and approximated human reproducibility. NLP may improve the efficiency of future multi-center clinical trials by accurately identifying clinical events at scale.

Impact of preoperative insomnia on poor postoperative pain control after elective spine surgery and the modified Calgary postoperative pain after spine surgery (MCAPPS) score.

Background: Approximately 30% to 64% of patients experience inadequate pain control following spine surgery. The Calgary postoperative pain after spine surgery (CAPPS) score was developed to identify this subset of patients. The impact of preoperative insomnia on postoperative pain control is unknown. This study aimed to investigate the relationship between preoperative insomnia and poor pain control after spine surgery, as well as improve the predictive accuracy of the CAPPS score. Methods: A prospective cohort study was conducted in patients undergoing elective spine surgery. Poor pain control was defined as a mean numeric rating scale pain score >4 at rest within the first 24-hours after surgery. Patients were evaluated using the CAPPS score, which included 7 prognostic factors. A multivariable logistic regression model was used to examine the association between preoperative insomnia severity index (ISI) and poor pain control, adjusting for the CAPPS score. The Modified CAPPS score was derived from this model. Results: Of 219 patients, 49.7% experienced poorly controlled pain. Prevalence of clinical insomnia (ISI≥15) was 26.9%. Preoperative ISI was independently associated with poor pain control (odds ratio [OR] 1.09, [95%CI=1.03-1.16], p=.004), after adjusting for the CAPPS score (OR 1.61, [95%CI=1.38-1.89], p<.001). The model exhibited good discrimination (c-statistics 0.80, [95%CI=0.74-0.86]) and calibration (Hosmer-Lemeshow chi-square=8.95, p=.35). The Modified CAPPS score also demonstrated good discrimination (c-statistic 0.78, [95%CI=0.72-0.84]) and calibration (Hosmer-Lemeshow chi-square=2.92, p=.57). Low-, high-, and extreme-risk groups stratified by the Modified CAPPS score had 17.3%, 49.1%, and 80.7% predicted probability of experiencing inadequate pain control compared to 32.0%, 64.0%, and 85.1% in the CAPPS score. Conclusions: Preoperative insomnia is prevalent and is a modifiable risk factor for poor pain control following spine surgery. Early identification and management of preoperative insomnia may lead to improved postoperative pain outcomes. Future external validation is needed to confirm the accuracy of the Modified CAPPS score.

Outpatient Worsening Among Patients With Mildly Reduced and Preserved Ejection Fraction Heart Failure in the DELIVER Trial.

BACKGROUND: Hospitalization is recognized as a sentinel event in the disease trajectory of patients with heart failure (HF), but not all patients experiencing clinical decompensation are ultimately hospitalized. Outpatient intensification of diuretics is common in response to symptoms of worsening HF, yet its prognostic and clinical relevance, specifically for patients with HF with mildly reduced or preserved ejection fraction, is uncertain. METHODS: In this prespecified analysis of the DELIVER trial (Dapagliflozin Evaluation to Improve the Lives of Patients With Preserved Ejection Fraction Heart Failure), we assessed the association between various nonfatal worsening HF events (those requiring hospitalization, urgent outpatient visits requiring intravenous HF therapies, and outpatient oral diuretic intensification) and rates of subsequent mortality. We further examined the treatment effect of dapagliflozin on an expanded composite end point of cardiovascular death, HF hospitalization, urgent HF visit, or outpatient oral diuretic intensification. RESULTS: In DELIVER, 4532 (72%) patients experienced no worsening HF event, whereas 789 (13%) had outpatient oral diuretic intensification, 86 (1%) required an urgent HF visit, 585 (9%) had an HF hospitalization, and 271 (4%) died of cardiovascular causes as a first presentation. Patients with a first presentation manifesting as outpatient oral diuretic intensification experienced rates of subsequent mortality that were higher (10 [8-12] per 100 patient-years) than those without a worsening HF event (4 [3-4] per 100 patient-years) but similar to rates of subsequent death after an urgent HF visit (10 [6-18] per 100 patient-years). Patients with an HF hospitalization as a first presentation of worsening HF had the highest rates of subsequent death (35 [31-40] per 100 patient-years). The addition of outpatient diuretic intensification to the adjudicated DELIVER primary end point (cardiovascular death, HF hospitalization, or urgent HF visit) increased the overall number of patients experiencing an event from 1122 to 1731 (a 54% increase). Dapagliflozin reduced the need for outpatient diuretic intensification alone (hazard ratio, 0.72 [95% CI, 0.64-0.82]) and when analyzed as a part of an expanded composite end point of worsening HF or cardiovascular death (hazard ratio, 0.76 [95% CI, 0.69-0.84]). CONCLUSIONS: In patients with HF with mildly reduced or preserved ejection fraction, worsening HF requiring oral diuretic intensification in ambulatory care was frequent, adversely prognostic, and significantly reduced by dapagliflozin. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03619213.

Renal and blood pressure effects of dapagliflozin in recently hospitalized patients with heart failure with mildly reduced or preserved ejection fraction: Insights from the DELIVER trial.

AIMS: Patients recently hospitalized for heart failure (HF) often have unstable haemodynamics and experience worsening renal failure, and are at elevated risk for recurrent HF events. In DELIVER, dapagliflozin reduced HF events or cardiovascular death including among patients who were hospitalized or recently hospitalized. METHODS AND RESULTS: We examined the effects of dapagliflozin versus placebo on estimated glomerular filtration rate (eGFR) slope (acute and chronic), 1-month change in systolic blood pressure, and the occurrence of serious hypovolaemic or renal adverse events in patients with and without HF hospitalization within 30 days of randomization. The 654 (90 randomized during hospitalization, 147 1-7 days post-discharge and 417 8-30 days post-discharge) recently hospitalized patients had lower baseline eGFR compared with those without recent HF hospitalization (median [interquartile range] 55 [43, 71] vs. 60 [47, 75] ml/min/1.73 m2 ). Dapagliflozin consistently reduced the risk of all-cause (pinteraction = 0.20), cardiac-related (pinteraction = 0.75), and HF-specific (pinteraction = 0.90) hospitalizations, irrespective of recent HF hospitalization. In those recently hospitalized, acute placebo-corrected eGFR reductions with dapagliflozin were modest and similar to patients without recent hospitalization (-2.0 [-4.1, +0.1] vs. -3.4 [-3.9, -2.9] ml/min/1.73 m2 , pinteraction = 0.12). Dapagliflozin's effect to slow chronic eGFR decline was similar regardless of recent hospitalization (pinteraction = 0.57). Dapagliflozin had a minimal effect on 1-month systolic blood pressure and to a similar degree in patients with and without recent hospitalization (-1.3 vs.-1.8 mmHg, pinteraction = 0.64). There was no treatment-related excess in renal or hypovolaemic serious adverse events, irrespective of recent HF hospitalization. CONCLUSION: In patients recently hospitalized with HF, initiation of dapagliflozin had minimal effects on blood pressure and did not increase renal or hypovolaemic serious adverse events, yet afforded long-term cardiovascular and kidney protective effects. These data suggest that the benefit to risk ratio favours initiation of dapagliflozin among stabilized patients hospitalized or recently hospitalized for HF. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT03619213.

Incremental prognostic value of biomarkers in PARADIGM-HF.

AIMS: It is uncertain how much candidate biomarkers improve risk prediction when added to comprehensive models including routinely collected clinical and laboratory variables in heart failure. METHODS AND RESULTS: Aldosterone, cystatin C, high-sensitivity troponin T (hs-TnT), galectin-3, growth differentiation factor-15 (GDF-15), kidney injury molecule-1, matrix metalloproteinase-2 and -9, soluble suppression of tumourigenicity-2, tissue inhibitor of metalloproteinase-1 (TIMP-1) and urinary albumin to creatinine ratio were measured in 1559 of PARADIGM-HF participants. We tested whether these biomarkers, individually or collectively, improved the performance of the PREDICT-HF prognostic model, which includes clinical, routine laboratory, and natriuretic peptide data, for the primary endpoint and cardiovascular and all-cause mortality. The mean age of participants was 67.3 ± 9.9 years, 1254 (80.4%) were men and 1103 (71%) were in New York Heart Association class II. During a mean follow-up of 30.7 months, 300 patients experienced the primary outcome and 197 died. Added individually, only four biomarkers were independently associated with all outcomes: hs-TnT, GDF-15, cystatin C and TIMP-1. When all biomarkers were added simultaneously to the PREDICT-HF models, only hs-TnT remained an independent predictor of all three endpoints. GDF-15 also remained predictive of the primary endpoint; TIMP-1 was the only other predictor of both cardiovascular and all-cause mortality. Individually or in combination, these biomarkers did not lead to significant improvements in discrimination or reclassification. CONCLUSIONS: None of the biomarkers studied individually or collectively led to a meaningful improvement in the prediction of outcomes over what is provided by clinical, routine laboratory, and natriuretic peptide variables.

Genetics of myocardial interstitial fibrosis in the human heart and association with disease.

Myocardial interstitial fibrosis is associated with cardiovascular disease and adverse prognosis. Here, to investigate the biological pathways that underlie fibrosis in the human heart, we developed a machine learning model to measure native myocardial T1 time, a marker of myocardial fibrosis, in 41,505 UK Biobank participants who underwent cardiac magnetic resonance imaging. Greater T1 time was associated with diabetes mellitus, renal disease, aortic stenosis, cardiomyopathy, heart failure, atrial fibrillation, conduction disease and rheumatoid arthritis. Genome-wide association analysis identified 11 independent loci associated with T1 time. The identified loci implicated genes involved in glucose transport (SLC2A12), iron homeostasis (HFE, TMPRSS6), tissue repair (ADAMTSL1, VEGFC), oxidative stress (SOD2), cardiac hypertrophy (MYH7B) and calcium signaling (CAMK2D). Using a transforming growth factor ß1-mediated cardiac fibroblast activation assay, we found that 9 of the 11 loci consisted of genes that exhibited temporal changes in expression or open chromatin conformation supporting their biological relevance to myofibroblast cell state acquisition. By harnessing machine learning to perform large-scale quantification of myocardial interstitial fibrosis using cardiac imaging, we validate associations between cardiac fibrosis and disease, and identify new biologically relevant pathways underlying fibrosis.

Missense Genetic Variation of ICAM1 and Incident Heart Failure.

BACKGROUND: Intercellular adhesion molecule-1 (ICAM-1) is a cell surface protein that participates in endothelial activation and is hypothesized to play a central role in heart failure (HF). We evaluated associations of ICAM1 missense genetic variants with circulating ICAM-1 levels and with incident HF. METHODS AND RESULTS: We identified 3 missense variants within ICAM1 (rs5491, rs5498 and rs1799969) and evaluated their associations with ICAM-1 levels in the Coronary Artery Risk Development in Young Adults Study and the Multi-Ethnic Study of Atherosclerosis (MESA). We determined the association among these 3 variants and incident HF in MESA. We separately evaluated significant associations in the Atherosclerosis Risk in Communities (ARIC) study. Of the 3 missense variants, rs5491 was common in Black participants (minor allele frequency [MAF] > 20%) and rare in other race/ethnic groups (MAF < 5%). In Black participants, the presence of rs5491 was associated with higher levels of circulating ICAM-1 at 2 timepoints separated by 8 years. Among Black participants in MESA (n = 1600), the presence of rs5491 was associated with an increased risk of incident HF with preserved ejection fraction (HFpEF; HR = 2.30; [95% CI 1.25-4.21; P = 0.007]). The other ICAM1 missense variants (rs5498 and rs1799969) were associated with ICAM-1 levels, but there were no associations with HF. In ARIC, rs5491 was significantly associated with incident HF (HR = 1.24 [95% CI 1.02 - 1.51]; P = 0.03), with a similar direction of effect for HFpEF that was not statistically significant. CONCLUSIONS: A common ICAM1 missense variant among Black individuals may be associated with increased risk of HF, which may be HFpEF-specific.

Virtual Care Team Guided Management of Patients With Heart Failure During Hospitalization.

BACKGROUND: Scalable and safe approaches for heart failure guideline-directed medical therapy (GDMT) optimization are needed. OBJECTIVES: The authors assessed the safety and effectiveness of a virtual care team guided strategy on GDMT optimization in hospitalized patients with heart failure with reduced ejection fraction (HFrEF). METHODS: In a multicenter implementation trial, we allocated 252 hospital encounters in patients with left ventricular ejection fraction ≤40% to a virtual care team guided strategy (107 encounters among 83 patients) or usual care (145 encounters among 115 patients) across 3 centers in an integrated health system. In the virtual care team group, clinicians received up to 1 daily GDMT optimization suggestion from a physician-pharmacist team. The primary effectiveness outcome was in-hospital change in GDMT optimization score (+2 initiations, +1 dose up-titrations, -1 dose down-titrations, -2 discontinuations summed across classes). In-hospital safety outcomes were adjudicated by an independent clinical events committee. RESULTS: Among 252 encounters, the mean age was 69 ± 14 years, 85 (34%) were women, 35 (14%) were Black, and 43 (17%) were Hispanic. The virtual care team strategy significantly improved GDMT optimization scores vs usual care (adjusted difference: +1.2; 95% CI: 0.7-1.8; P < 0.001). New initiations (44% vs 23%; absolute difference: +21%; P = 0.001) and net intensifications (44% vs 24%; absolute difference: +20%; P = 0.002) during hospitalization were higher in the virtual care team group, translating to a number needed to intervene of 5 encounters. Overall, 23 (21%) in the virtual care team group and 40 (28%) in usual care experienced 1 or more adverse events (P = 0.30). Acute kidney injury, bradycardia, hypotension, hyperkalemia, and hospital length of stay were similar between groups. CONCLUSIONS: Among patients hospitalized with HFrEF, a virtual care team guided strategy for GDMT optimization was safe and improved GDMT across multiple hospitals in an integrated health system. Virtual teams represent a centralized and scalable approach to optimize GDMT.

Machine Learning to Understand Genetic and Clinical Factors Associated With the Pulse Waveform Dicrotic Notch.

BACKGROUND: Absence of a dicrotic notch on finger photoplethysmography is an easily ascertainable and inexpensive trait that has been associated with age and prevalent cardiovascular disease. However, the trait exists along a continuum, and little is known about its genetic underpinnings or prognostic value for incident cardiovascular disease. METHODS: In 169 787 participants in the UK Biobank, we identified absent dicrotic notch on photoplethysmography and created a novel continuous trait reflecting notch smoothness using machine learning. Next, we determined the heritability, genetic basis, polygenic risk, and clinical relations for the binary absent notch trait and the newly derived continuous notch smoothness trait. RESULTS: Heritability of the continuous notch smoothness trait was 7.5%, compared with 5.6% for the binary absent notch trait. A genome-wide association study of notch smoothness identified 15 significant loci, implicating genes including NT5C2 (P=1.2×10-26), IGFBP3 (P=4.8×10-18), and PHACTR1 (P=1.4×10-13), compared with 6 loci for the binary absent notch trait. Notch smoothness stratified risk of incident myocardial infarction or coronary artery disease, stroke, heart failure, and aortic stenosis. A polygenic risk score for notch smoothness was associated with incident cardiovascular disease and all-cause death in UK Biobank participants without available photoplethysmography data. CONCLUSIONS: We found that a machine learning derived continuous trait reflecting dicrotic notch smoothness on photoplethysmography was heritable and associated with genes involved in vascular stiffness. Greater notch smoothness was associated with greater risk of incident cardiovascular disease. Raw digital phenotyping may identify individuals at risk for disease via specific genetic pathways.

Validation of the Calgary Postoperative Pain after Spine Surgery Score for Poor Postoperative Pain Control after Spine Surgery.

OBJECTIVE: The Calgary Postoperative Pain after Spine Surgery (CAPPS) score was developed to identify patients at risk of experiencing poorly controlled pain after spine surgery. The goal of this study was to independently validate the CAPPS score on a prospectively collected patient sample. METHODS: Poor postoperative pain control was defined as a mean numeric rating scale (NRS) for pain >4 at rest in the first 24 hours after surgery. Baseline characteristics in this study (validation cohort) were compared to those of the development cohort used to create the CAPPS score. Predictive performance of the CAPPS score was assessed by the area under the curve (AUC) and percentage misclassification for discrimination. A graphical comparison between predicted probability vs. observed incidence of poorly controlled pain was performed for calibration. RESULTS: Fifty-two percent of 201 patients experienced poorly controlled pain. The validation cohort exhibited lower depression scores and a higher proportion using daily opioid medications compared to the development cohort. The AUC was 0.74 [95%CI = 0.68-0.81] in the validation cohort compared to 0.73 [95%CI = 0.69-0.76] in the development cohort for the eight-tier CAPPS score. When stratified between the low- vs. extreme-risk and low- vs. high-risk groups, the percentage misclassification was 21.2% and 30.7% in the validation cohort, compared to 29.9% and 38.0% in the development cohort, respectively. The predicted probability closely mirrored the observed incidence of poor pain control across all scores. CONCLUSIONS: The CAPPS score, based on seven easily obtained and reliable prognostic variables, was validated using a prospectively collected, independent sample of patients.

Cardiac Xenotransplantation: Challenges, Evolution, and Advances.

The increased need for heart transplantation in patients with advanced heart failure has introduced demand for a greater supply of donor hearts. Progress in cross-species experimental models has led to promise for ushering in the clinical use of xenotransplantation (XTx) as a potential solution to the organ shortage worldwide. In this review, the authors first highlight the historical advances that led to the first pig-to-human heart transplantation, a landmark moment in the field of advanced heart failure. The authors discuss immunologic, infectious, and physiological challenges for implementation of XTx, as well as innovations in the science of genetic manipulation that allowed clinical translation of this therapy. The authors consider ongoing barriers that affect ongoing translation of this technology into clinical care in the current era. Finally, the authors propose a framework for advancing clinical application of XTx.

Dapagliflozin in Patients Recently Hospitalized With Heart Failure and Mildly Reduced or Preserved Ejection Fraction.

BACKGROUND: Patients recently hospitalized for heart failure (HF) are at high risk for rehospitalization and death. OBJECTIVES: The purpose of this study was to investigate clinical outcomes and response to dapagliflozin in patients with HF with mildly reduced or preserved left ventricular ejection fraction (LVEF) who were enrolled during or following hospitalization. METHODS: The DELIVER (Dapagliflozin Evaluation to Improve the LIVES of Patients With PReserved Ejection Fraction Heart Failure) trial randomized patients with HF and LVEF >40% to dapagliflozin or placebo. DELIVER permitted randomization during or shortly after hospitalization for HF in clinically stable patients off intravenous HF therapies. This prespecified analysis investigated whether recent HF hospitalization modified risk of clinical events or response to dapagliflozin. The primary outcome was worsening HF event or cardiovascular death. RESULTS: Of 6,263 patients in DELIVER, 654 (10.4%) were randomized during HF hospitalization or within 30 days of discharge. Recent HF hospitalization was associated with greater risk of the primary outcome after multivariable adjustment (HR: 1.88; 95% CI: 1.60-2.21; P < 0.001). Dapagliflozin reduced the primary outcome by 22% in recently hospitalized patients (HR: 0.78; 95% CI: 0.60-1.03) and 18% in patients without recent hospitalization (HR: 0.82; 95% CI: 0.72-0.94; Pinteraction = 0.71). Rates of adverse events, including volume depletion, diabetic ketoacidosis, or renal events, were similar with dapagliflozin and placebo in recently hospitalized patients. CONCLUSIONS: Dapagliflozin safely reduced risk of worsening HF or cardiovascular death similarly in patients with and without history of recent HF hospitalization. Starting dapagliflozin during or shortly after HF hospitalization in patients with mildly reduced or preserved LVEF appears safe and effective. (Dapagliflozin Evaluation to Improve the LIVEs of Patients With PReserved Ejection Fraction Heart Failure [DELIVER]; NCT03619213).